Machine Learning & Artificial Intelligence Engineering Internship – Summer 2027
Originally posted 18 September 2026 by the employer — open 1 day.
About the role
As a Machine Learning / AI Engineering Intern, you will help build solutions and tools for mobile and embedded machine learning platforms. These platforms power smartphones, autonomous vehicles, robotics, and IoT devices.
What you'll do
- Design, develop, and test software for machine learning tools and frameworks.
- Make models smaller and more efficient for edge devices.
- Work with popular neural network frameworks.
- Gain exposure to Qualcomm’s SOC compute and ML hardware accelerators.
- Contribute to projects focusing on AI systems infrastructure, distributed inference platforms, compiler technologies, runtime systems, GPU acceleration, model serving, performance optimization, and large-scale deployment of machine learning workloads.
What you'll need
- Currently enrolled in a bachelor’s, master’s, or Ph.D. degree program in computer engineering, computer science, electrical engineering, or a related field.
- Availability for 11–14 weeks during Summer 2027 (May–September).
- Expected graduation date of November 2027 or later.
- 1 year of experience with programming languages such as C, C++, Python.
Nice to have
- Currently enrolled in a Master’s or PhD degree program in computer engineering, computer science, electrical engineering, or a related field.
- Proficiency in deep neural networks, machine learning algorithms, and architectures (CNNs, RNNs, LSTMs).
- Experience with ML frameworks like TensorFlow, TFLite, PyTorch.
- Skills in neural network programming, video/image processing, and application development.
- Knowledge of compiler frameworks (LLVM, GCC, TVM, XLA) and parallel computing.
- Experience with AI infrastructure, inference systems, distributed computing, runtime systems, GPU programming, CUDA, Kubernetes, MLIR, or performance optimization of machine learning workloads.
- Understanding of linear algebra operations and fast math libraries.
- Theoretical knowledge of ML, deep learning, model compression, quantization, and optimization.
- Experience with reinforcement learning, neural architecture search, kernel optimization, Bayesian optimization.
- Familiarity with on-device training, transfer learning, personalization, federated learning, NLP, and ML security/privacy.
- Experience with deep generative models, audio/speech processing, NLP, computer vision, and wireless communication.
- Background in ML data pipelines, data management, backend/frontend applications.
- Research excellence with publications in NeurIPS, CVPR, ICML, ICLR, ICCV.
- Experience in object-oriented software design (OOSD).
Skills: machine learning platforms, neural network frameworks, SOC compute, ML hardware accelerators, AI systems infrastructure
This role has been open 0 days — well below the 65-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
518
|
Median days open
65 d
|
Median salary
$229k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Qualcomm | All employers we track in this specialty (518 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 106 | 518 |
| Open roles in the wider Software, Firmware & Systems family | 722 | 5796 · 143 employers |
| Median days open | 97 d | 65 d (+32 d vs this employer) |
| Median salary (USD postings) | — | $229k |
Skills observed across this category: machine learning platforms, neural network frameworks, SOC compute, ML hardware accelerators, AI systems infrastructure
Who's hiring in this category
- Qualcomm (this employer) · 106 open roles · median 97 d
- NVIDIA · 85 open roles · median 65 d
- AMD · 43 open roles · median 60 d
- Micron Technology · 32 open roles · median 37 d
- Mobileye · 25 open roles · median 51 d
- Analog Devices · 14 open roles · median 22 d
How we counted: 518 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 employers tracked in the SemiconductorJobs index, counted 19 Sept 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.